




"""simple docstring"""




from __future__ import annotations

from typing import Any






class        __magic_name__				:






				'''simple docstring'''





				def __init__(			self						,					_a = 6					):





							"""simple docstring"""
							lowerCamelCase      =   None
							lowerCamelCase      =   None
							self.create_linked_list(_a					)





				def   _lowerCAmelCase							(			self						,					_a					):





							"""simple docstring"""
							lowerCamelCase      =   Node()
							lowerCamelCase      =   current_node
							lowerCamelCase      =   current_node
							lowerCamelCase      =   current_node
							for _ in range(1						,					_a					):
										lowerCamelCase      =   Node()
										lowerCamelCase      =   current_node
										lowerCamelCase      =   previous_node
										lowerCamelCase      =   current_node
							lowerCamelCase      =   self.front
							lowerCamelCase      =   previous_node





				def   _lowerCAmelCase							(			self					):





							"""simple docstring"""
							return (
							    self.front == self.rear
							    and self.front is not None
							    and self.front.data is None
							)





				def   _lowerCAmelCase							(			self					):





							"""simple docstring"""
							self.check_can_perform_operation()
							return self.front.data if self.front else None





				def   _lowerCAmelCase							(			self						,					_a					):





							"""simple docstring"""
							if self.rear is None:
										return

							self.check_is_full()
							if not self.is_empty():
										lowerCamelCase      =   self.rear.next
							if self.rear:
										lowerCamelCase      =   data





				def   _lowerCAmelCase							(			self					):





							"""simple docstring"""
							self.check_can_perform_operation()
							if self.rear is None or self.front is None:
										return None
							if self.front == self.rear:
										lowerCamelCase      =   self.front.data
										lowerCamelCase      =   None
										return data

							lowerCamelCase      =   self.front
							lowerCamelCase      =   old_front.next
							lowerCamelCase      =   old_front.data
							lowerCamelCase      =   None
							return data





				def   _lowerCAmelCase							(			self					):





							"""simple docstring"""
							if self.is_empty():
										raise Exception("""Empty Queue"""					)





				def   _lowerCAmelCase							(			self					):





							"""simple docstring"""
							if self.rear and self.rear.next == self.front:
										raise Exception("""Full Queue"""					)






class        __magic_name__				:






				'''simple docstring'''





				def __init__(			self					):





							"""simple docstring"""
							lowerCamelCase      =   None
							lowerCamelCase      =   None
							lowerCamelCase      =   None


if __name__ == "__main__":
					import doctest

					doctest.testmod()









"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowerCAmelCase				:     Optional[int]					=				{"""configuration_swin""": ["""SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SwinConfig""", """SwinOnnxConfig"""]}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase				:     int					=				[
					    """SWIN_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """SwinForImageClassification""",
					    """SwinForMaskedImageModeling""",
					    """SwinModel""",
					    """SwinPreTrainedModel""",
					    """SwinBackbone""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase				:     str					=				[
					    """TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TFSwinForImageClassification""",
					    """TFSwinForMaskedImageModeling""",
					    """TFSwinModel""",
					    """TFSwinPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_swin import (
										    SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SwinBackbone,
										    SwinForImageClassification,
										    SwinForMaskedImageModeling,
										    SwinModel,
										    SwinPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_swin import (
										    TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFSwinForImageClassification,
										    TFSwinForMaskedImageModeling,
										    TFSwinModel,
										    TFSwinPreTrainedModel,
										)

else:
					import sys

					lowerCAmelCase				:     int					=				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



